Global Positioning System (GPS) technology has become an integral part of our daily activities. However, on most occasions GPS signals can be unreliable or unavailable. Additionally, land vehicles are especially prone to accidental or deliberated GPS interference, which can be disadvantageous to the user. Therefore, the need for a localization system that can not only localize in the absence of GPS signals but also provide services when GPS signals are spoofed is clearly evident.
Apart from GPS based systems, other radio frequency (RF) based localization systems also currently exist. These RF based systems have beacon based or anchor based systems, and are dependent on time of arrival, time difference of arrival, and angle of arrival. However, these methods require expensive hardware for prototyping, a complex time synchronization step, one or more directional antennas, and/or omnidirectional antennas or have problems with multipath.
In addition to the mentioned methods, other distance-dependent features of the RF signal can also be used for localization. As an example, Received Signal Strength Indicator (RSSI), Audio Signal-to-Noise Ratio (SNR), and Stereo Channel Separation (SCS) are also used for GPS free environments. RSSI is known for its cost effectiveness and low computation complexity. However, SNR and SCS have relatively high computational complexity which is disadvantageous.
The objective of the present invention is to address the aforementioned issues. More specifically, the present invention intends to introduce a simple and fast localization algorithm that can localize within a very large area in the absence of a GPS or in the presence of a degraded GPS. In doing so, the present invention has the potential to addresses the low accuracy issues in GPS degraded environments and the slow information processing speeds during initialization of the GPS system. Therefore, by utilizing the present invention in a GPS degraded environment, the user can determine the location with increased accuracy and fast initialization speeds. The present invention is based on analyzing the RSSI obtained using a very cheap hardware and thus the hardware costs are lowered. The present invention uses algorithms for processing the RSSI without explicit analysis of the signal-to-noise ratio (SNR) and/or stereo channel separation (SCS) and hence in turn reduces computation complexity.